Maintenance Management

Class overview

A COURSE THAT PROVIDES SAVINGS AND EFFICIENCY

Contents

The maintenance of industrial plants is an increasingly strategic asset: the efficiency and productivity of the entire supply chain depend on it! Thanks to the intervention of highly competent and specialized technicians, this course will allow you to learn and experience the most advanced techniques to manage the maintenance of the plants, in particular for the production of dry pasta and extruded products. It will deal not only with the best practices for a correct ordinary maintenance, but also with the most advanced solutions that allow preventive intervention on the plant to guarantee its good functioning in time, avoiding production interruptions or drops in performance. A proper maintenance therefore means a reduction in overall management costs and fewer operating problems.

The presentations will be complemented by practical examples thanks to the collaboration with Pastificio Campioni (Italy), a high-tech pasta factory exclusively equipped with Pavan lines, which has allowed us to carry out complete and detailed technical investigations.

Big Data for a manufacturing 4.0
• Data analysis to assess process quality
• Using data to create a baseline of reference
• Analysis of the variable(s) that identify the quality of the process
• Identification of the parameters that influence the value of the variables of the first point – correlation matrix
• Definition of the process to be evaluated
• Implementation of a predictive model for the evaluation of the defined variable and validation
• Identification of periods with efficient or less efficient behavior based on data history
• Data analysis to evaluate machine downtime
• How to collect data from machines and how to analyse them
• What infrastructures are needed to collect data from machines, analyse and valorise them
• How to analyze production process variables to develop quality or performance predictive analysis
• How to evaluate internal capabilities
• What infrastructure, equipment and resources are needed?
• How to find the necessary external capabilities
• Specific examples in the food production sector

Efficiency and maintenance of centrifugal pumps: how to choose a centrifugal pump, typical curves of a pump, behavior at starting, operating and adjustment status, maintenance and troubleshooting

Practical experiences on the management of maintenance techniques

March

28

Big Data for a manufacturing 4.0
• Data analysis to assess process quality
• Using data to create a baseline of reference
• Analysis of the variable(s) that identify the quality of the process
• Identification of the parameters that influence the value of the variables of the first point – correlation matrix
• Definition of the process to be evaluated
• Implementation of a predictive model for the evaluation of the defined variable and validation
• Identification of periods with efficient or less efficient behavior based on data history
• Data analysis to evaluate machine downtime
• How to collect data from machines and how to analyse them
• What infrastructures are needed to collect data from machines, analyse and valorise them
• How to analyze production process variables to develop quality or performance predictive analysis
• How to evaluate internal capabilities
• What infrastructure, equipment and resources are needed?
• How to find the necessary external capabilities
• Specific examples in the food production sector

Contents
• Data analysis to assess process quality
• Using data to create a baseline of reference
• Analysis of the variable(s) that identify the quality of the process
• Identification of the parameters that influence the value of the variables of the first point – correlation matrix
• Definition of the process to be evaluated
• Implementation of a predictive model for the evaluation of the defined variable and validation
• Identification of periods with efficient or less efficient behavior based on data history
• Data analysis to evaluate machine downtime
• How to collect data from machines and how to analyse them
• What infrastructures are needed to collect data from machines, analyse and valorise them
• How to analyze production process variables to develop quality or performance predictive analysis
• How to evaluate internal capabilities
• What infrastructure, equipment and resources are needed?
• How to find the necessary external capabilities
• Specific examples in the food production sector